Within image processing there is a continuing effort put into reducing bit rate or image size while maintaining a perceived quality of an image. Typically, for monitoring purposes, when encoding the image, an object having motion may in many cases be prioritized in some way in relation to a static object, e.g. parts of the image comprising a walking human will be allocated a higher bit rate (lower degree of compression) than parts of the image comprising the pavement which the human walks on. In many cases, this is an advantageous way of encoding the image, but in some cases it may result in that parts of the image comprising uninteresting but moving objects such as moving leaves of a tree will be encoded with a lower degree of compression, and thus consume unnecessary bit rate (for no use). Also noise in the image may be identified, wrongly, as motion and consume bitrate. A poor image quality due to e.g. darkness, rain, snow, or fog may also give similar problems.
There is thus a need for improvements within this context.